performance

Introduction The python library numba provides (among others) just-in-time (jit) compilation for python. Python code can gain tremendous speed-ups without the need to rewrite a single line of code. Simply adding a decorator to a function such as illustrated in this example: import numba @njit def accelerate_me(): ... can lead to run times comparable to C or Fortran code. Let's make a concrete example, where we add random numbers in a for loop (not advised, but used here to demonstrate numba). [Read More]